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Detection method for transparent window cleaning device, image processing approach
Recent years, there has been an increase in the number of high-rise buildings, and subsequently, the interest in external wall cleaning methods has similarly increased. While a number of exterior wall cleaning robots are being developed, a method to detect contaminants on the exterior walls is still...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881614/ https://www.ncbi.nlm.nih.gov/pubmed/35217716 http://dx.doi.org/10.1038/s41598-022-07235-y |
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author | Lee, Jiseok Chae, Hobyeong Kim, KyungMin Kim, Hwa Soo Seo, TaeWon |
author_facet | Lee, Jiseok Chae, Hobyeong Kim, KyungMin Kim, Hwa Soo Seo, TaeWon |
author_sort | Lee, Jiseok |
collection | PubMed |
description | Recent years, there has been an increase in the number of high-rise buildings, and subsequently, the interest in external wall cleaning methods has similarly increased. While a number of exterior wall cleaning robots are being developed, a method to detect contaminants on the exterior walls is still required. The exteriors of most high-rise buildings today take the form of a window curtain-wall made of translucent glass. Detecting dust on translucent glass is a significant challenge. Here, we have attempted to overcome this challenge using image processing, inspired by the fact that people typically use just the ‘naked eye’ to recognize dust on windows. In this paper, we propose a method that detects dust through simple image processing techniques and estimates its density. This method only uses processing techniques that are not significantly restricted by global brightness and background, making it easily applicable in outdoor conditions. Dust separation was performed using a median filter, and dust density was estimated through a mean shift analysis technique. This dust detection method can perform dust separation and density estimation using only an image of the dust on a translucent window with blurry background. |
format | Online Article Text |
id | pubmed-8881614 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88816142022-03-01 Detection method for transparent window cleaning device, image processing approach Lee, Jiseok Chae, Hobyeong Kim, KyungMin Kim, Hwa Soo Seo, TaeWon Sci Rep Article Recent years, there has been an increase in the number of high-rise buildings, and subsequently, the interest in external wall cleaning methods has similarly increased. While a number of exterior wall cleaning robots are being developed, a method to detect contaminants on the exterior walls is still required. The exteriors of most high-rise buildings today take the form of a window curtain-wall made of translucent glass. Detecting dust on translucent glass is a significant challenge. Here, we have attempted to overcome this challenge using image processing, inspired by the fact that people typically use just the ‘naked eye’ to recognize dust on windows. In this paper, we propose a method that detects dust through simple image processing techniques and estimates its density. This method only uses processing techniques that are not significantly restricted by global brightness and background, making it easily applicable in outdoor conditions. Dust separation was performed using a median filter, and dust density was estimated through a mean shift analysis technique. This dust detection method can perform dust separation and density estimation using only an image of the dust on a translucent window with blurry background. Nature Publishing Group UK 2022-02-25 /pmc/articles/PMC8881614/ /pubmed/35217716 http://dx.doi.org/10.1038/s41598-022-07235-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lee, Jiseok Chae, Hobyeong Kim, KyungMin Kim, Hwa Soo Seo, TaeWon Detection method for transparent window cleaning device, image processing approach |
title | Detection method for transparent window cleaning device, image processing approach |
title_full | Detection method for transparent window cleaning device, image processing approach |
title_fullStr | Detection method for transparent window cleaning device, image processing approach |
title_full_unstemmed | Detection method for transparent window cleaning device, image processing approach |
title_short | Detection method for transparent window cleaning device, image processing approach |
title_sort | detection method for transparent window cleaning device, image processing approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881614/ https://www.ncbi.nlm.nih.gov/pubmed/35217716 http://dx.doi.org/10.1038/s41598-022-07235-y |
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